Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering.
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| Title: | Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering. |
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| Authors: | van den Beemt, Antoine1, Buys, Joos1, van der Aalst, Wil2 |
| Source: | International Review of Research in Open & Distributed Learning. Nov2018, Vol. 19 Issue 5, p37-60. 24p. 7 Diagrams, 6 Charts, 7 Graphs. |
| Subject Terms: | *Massive open online courses, *Structural learning theory, *Distance education, *Constructivism (Education), Process mining, Cluster analysis (Statistics) |
| Abstract: | The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students' activities in a MOOC from the perspective of personal constructivism, which we operationalized as a combination of learning behaviour and learning progress. This study considers students' data analyzed as per the MOOC Process Mining: Data Science in Action. We explore the relation between learning behaviour and learning progress in MOOCs, with the purpose to gain insight into how passing and failing students distribute their activities differently along the course weeks, rather than predict students' grades from their activities. Commonly-studied aggregated counts of activities, specific course item counts, and order of activities were examined with cluster analyses, means analyses, and process mining techniques. We found four meaningful clusters of students, each representing specific behaviour ranging from only starting to fully completing the course. Process mining techniques show that successful students exhibit a more steady learning behaviour. However, this behaviour is much more related to actually watching videos than to the timing of activities. The results offer guidance for teachers. [ABSTRACT FROM AUTHOR] |
| Copyright of International Review of Research in Open & Distributed Learning is the property of Governors of Athabasca University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 133476349 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=133476349 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.19173/irrodl.v19i5.3748 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 37 Subjects: – SubjectFull: Massive open online courses Type: general – SubjectFull: Structural learning theory Type: general – SubjectFull: Distance education Type: general – SubjectFull: Constructivism (Education) Type: general – SubjectFull: Process mining Type: general – SubjectFull: Cluster analysis (Statistics) Type: general Titles: – TitleFull: Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: van den Beemt, Antoine – PersonEntity: Name: NameFull: Buys, Joos – PersonEntity: Name: NameFull: van der Aalst, Wil IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 14923831 Numbering: – Type: volume Value: 19 – Type: issue Value: 5 Titles: – TitleFull: International Review of Research in Open & Distributed Learning Type: main |
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